Document Type
Article - On Campus Only
Publication Date
2013
Abstract
This study investigates the impact of teacher characteristics and instructional strategies on the mathematics achievement of students in kindergarten and first grade and tackles the question of how best to use longitudinal survey data to elicit causal inference in the face of potential threats to validity due to nonrandom assignment to treatment. We develop a step-by-step approach to selecting a modeling and estimation strategy and find that teacher certification and courses in methods of teaching mathematics have a slightly negative effect on student achievement in kindergarten, whereas postgraduate education has a positive effect in first grade. Various teaching modalities, such as working with counting manipulatives, using math worksheets, and completing problems on the chalkboard, have positive effects on achievement in kindergarten, and pedagogical practices relating to explaining problem solving and working on problems from textbooks have positive effects on achievement in first grade. We show that the conclusions drawn depend on the estimation and modeling choices made and that several prior studies of teacher effects using longitudinal survey data likely neglected important features needed to establish causal inference.
Original Publication Citation
Cassandra Guarino, Steven G. Dieterle, Anna E. Bargagliotti & William M. Mason (2013) What Can We Learn About Effective Early Mathematics Teaching? A Framework for Estimating Causal Effects Using Longitudinal Survey Data, Journal of Research on Educational Effectiveness, 6:2, 164-198, DOI: 10.1080/19345747.2012.706695
Digital Commons @ LMU & LLS Citation
Bargagliotti, Anna E., "What Can We Learn about Effective Early Mathematics Teaching? A Framework for Estimating Causal Effects using Longitudinal Survey Data" (2013). Mathematics, Statistics and Data Science Faculty Works. 137.
https://digitalcommons.lmu.edu/math_fac/137
